Subarray pattern based grating lobe interference suppression method

Abstract

The application discloses a grating lobe interference suppression method based on a subarray direction pattern, and the implementation steps are as follows: generating a planar array signal including grating lobe angle interference signals and noise; calculating the weight of each subarray after the planar array is uniformly divided; designing the direction pattern of each subarray; and suppressing grating lobe interference. The application can make the subarray direction pattern produce a wide null at the grating lobe angle corresponding to the subarray level direction pattern, thereby suppressing grating lobe interference. The application has the advantages that it can suppress both known-angle grating lobe interference and unknown-angle grating lobe interference, has high application universality, improves the output signal-to-noise ratio of subarray level adaptive beam forming when grating lobe interference exists, and solves the problems that the angle information of grating lobe interference needs to be known when radar subarray level adaptive beam forming exists, which leads to the inability to suppress other grating lobe angle interference and the loss of useful signals, resulting in the reduction of the output signal-to-noise ratio.

Description

Technical Field

[0001] This invention belongs to the field of radar technology, and more specifically relates to a grating lobe interference suppression method based on subarray radiation patterns within the field of radar interference suppression technology. This invention can be used to suppress grating lobe interference from radar subarray-level adaptive beamforming countermeasures. Background Technology

[0002] In radar technology applications, when a radar is in an environment with strong active interference, the wide angular coverage of the antenna's sidelobes allows interference signals to easily enter the receiver from the sidelobes, obscuring the desired signal and hindering target detection and subsequent signal processing. Adaptive digital beamforming technology enables phased array radars to adaptively suppress interference signals and retain the desired signal based on environmental information, significantly improving the radar system's anti-interference capability. However, adaptive array antennas typically have a large number of sensor elements. If full-element digital reception is used, the large number of channels and the computational load of the adaptive algorithm make it difficult to generate a fast adaptive response. Furthermore, an equal number of A / D conversions and weighted processing steps are required, significantly increasing the system's hardware cost. Therefore, in practical engineering implementations, a subarray synthesis scheme is often used, combining several array antenna elements into a single channel to reduce the dimensionality of the signal processor, followed by subarray-level digital beamforming. The simplest method for subarray partitioning is the uniform partitioning method, but this method has obvious drawbacks. The effective phase center spacing of each subarray usually exceeds half a wavelength, and grating lobes will be generated between subarrays. When there is interference entering from the grating lobe angle, the subarray-level adaptive beamforming will cause the loss of useful signal, which will worsen the anti-interference performance of the system.

[0003] The 27th Research Institute of China Electronics Technology Group Corporation disclosed a method for solving grating lobe interference in radar digital beamforming in its patent application "A Digital Beamforming Method for Solving Grating Lobe Interference Problem" (application no. 201611244720.8, application date 2016.12.29, publication no. CN106842147 A). The method comprises the following steps: First, the signal is processed into subarray-level channel signals using a unit-level phase shifter combined with a power divider network; second, the subarray-level channel signals are converted into baseband signals through analog-to-digital conversion and digital quadrature demodulation; third, a blocking matrix is ​​constructed using the angle information of the grating lobe interference, and the blocking of the grating lobe interference signal is completed in the DSP on the digital beamforming processing board, and the weight vector is calculated using the blocked signal; fourth, the FPGA on the digital beamforming processing board performs weighted processing to form the final receiving beam. Although this method can suppress grating lobe interference in radar digital beamforming, it still has a shortcoming: the angle information of the grating lobe interference signal is required when constructing the blocking matrix. The blocking matrix can only block grating lobe interference signals with known angles and cannot suppress interference signals with other grating lobe angles.

[0004] Harbin Engineering University disclosed a method for suppressing grating lobes in broadband beamforming of sparse arrays in its patent application "A method for suppressing grating lobes in broadband beamforming of sparse arrays" (application number 201510616319.1, application date 2015.09.24, publication number CN 105334508 A). The method involves the following steps: First, performing frequency domain broadband beamforming processing on the array signals received by multiple array elements of the sparse array; second, utilizing the azimuth θ of the strong interference target signal obtained in the first step... k The third step involves predicting the grating lobe angle based on the grating lobe angle obtained in the second step. The fourth step involves calculating the grating lobe start and end ranges at each frequency point based on the main lobe width obtained in the third step. k Fifth step, using the grating lobe suppression weight coefficient matrix W obtained in step four. k The grating lobes are suppressed using the spatial spectrum output matrix P obtained in the first step for each frequency point; in the sixth step, the spatial spectrum output matrix P after grating lobe suppression in the fifth step is added together. out The summation is used for broadband spatial spectrum synthesis. Although this method solves the problem of grating lobe interference in broadband beamforming caused by general equidistant sparse arrays, it still has shortcomings. The grating lobe suppression weighting coefficient matrix is ​​applied to the spatial spectrum output matrix after beamforming. When grating lobe interference exists, useful signals will be lost during the subarray-level adaptive beamforming process, reducing the output signal-to-noise ratio of the subarray-level adaptive beamforming. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of the prior art by proposing a grating lobe interference suppression method based on subarray radiation patterns. This method solves the problem that suppressing grating lobe interference requires knowing the angle information of the grating lobe interference, which leads to the inability to suppress other grating lobe angle interferences. It also addresses the problem that radar subarray-level adaptive beamforming loses useful signals when grating lobe interference is present, resulting in a decrease in the output signal-to-noise ratio of subarray-level adaptive beamforming.

[0006] The approach to achieving the objective of this invention is as follows: This invention generates a planar array signal including grating lobe angle interference signals and noise. Using the subarray signals corresponding to the array elements within the subarray signal, the weights of each subarray are calculated according to the Minimum Variance Distortionless Response (MVDR) method. These weights are then used to design the subarray radiation pattern, creating wide nulls in the grating lobe angle region corresponding to the subarray-level radiation pattern. This effectively suppresses grating lobe interference within the grating lobe angle region, thus solving the problem that suppressing grating lobe interference requires knowledge of the grating lobe angle information, which prevents the suppression of other grating lobe angle interference. After designing the subarray radiation pattern, this invention utilizes the subarray with wide nulls in the grating lobe angle of the subarray radiation pattern to receive the incoming signal, suppressing grating lobe interference in the incoming signal and improving the output signal-to-noise ratio of subarray-level adaptive beamforming in the presence of grating lobe interference. This solves the problem that the loss of useful signal in radar subarray-level adaptive beamforming due to grating lobe interference leads to a decrease in the output signal-to-noise ratio.

[0007] The technical solution for achieving the objective of this invention includes the following steps:

[0008] Step 1: Generate a planar array signal including grid lobe angle interference signal and noise;

[0009] Step 2: Calculate the weight of each subarray after uniformly dividing the planar array:

[0010] Step 2.1: Calculate the autocorrelation matrix of each subarray signal;

[0011] Step 2.2: Calculate the steering vector corresponding to different azimuth and elevation angles for the desired signal received by each array element in the subarray;

[0012] Step 2.3: Calculate the weight of each subarray;

[0013] Step 3, design the orientation pattern for each subarray:

[0014] Step 3.1, calculate the response amplitude of each subarray for each azimuth and elevation angle within the observation angle range according to the following formula:

[0015]

[0016] in, This indicates that the m-th subarray corresponds to an azimuth angle of θ' and an elevation angle of θ'. The response amplitude, w m Let H represent the weights of the m-th subarray, and let H denote the conjugate transpose operation. This indicates that the azimuth angle θ' and elevation angle of the signal received by the array element in the m-th subarray are... The guide vector;

[0017] Step 3.2: Connect the response amplitudes of each subarray to each azimuth and elevation angle in sequence within the observation angle range of [-90°, 90°] to obtain the radiation pattern of the subarray;

[0018] Step 4, suppress grid lobe interference:

[0019] Step 4.1: Establish a dimension reduction transformation matrix. The number of rows in this matrix is ​​equal to the number of array elements in the planar array, and the number of columns in this matrix is ​​equal to the number of subarrays into which the planar array is divided.

[0020] Step 4.2: According to the subarray synthesis formula, the elements in the weight of each subarray are multiplied and accumulated with the incoming wave signal received by the corresponding array element in the subarray of the incoming wave signal received by the planar array to obtain the subarray-level received signal, thereby suppressing the grating lobe interference in the incoming wave signal.

[0021] Compared with the prior art, the present invention has the following advantages:

[0022] First, this invention generates a planar array signal including grating lobe angle interference signals and noise. Using the subarray signals corresponding to the subarray elements within the planar array signal, weights are calculated according to the MVDR method. These weights are then used to design the subarray radiation pattern, creating a wide null in the grating lobe angle region corresponding to the subarray level radiation pattern. This effectively suppresses grating lobe interference within the grating lobe angle region, overcoming the shortcomings of existing technologies where suppressing grating lobe interference requires known angle information, thus preventing the suppression of other grating lobe angle interferences. This invention not only suppresses grating lobe interference when the angle information is known but also when the angle is unknown, improving the universality of application.

[0023] Secondly, by designing the subarray radiation pattern, this invention generates a wide null in the grating lobe angle region corresponding to the subarray-level radiation pattern. By using the subarray with the wide null in the subarray radiation pattern to receive the incoming signal, grating lobe interference in the incoming signal can be suppressed. After suppressing grating lobe interference, subarray-level adaptive beamforming is performed. This overcomes the defect in the prior art where radar subarray-level adaptive beamforming loses useful signals under the condition of grating lobe interference, resulting in a decrease in the output signal-to-noise ratio of adaptive subarray-level beamforming. This invention enables the invention to suppress grating lobe interference while protecting the useful signal, and improves the output signal-to-noise ratio of subarray-level adaptive beamforming in the presence of grating lobe interference. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the implementation of the present invention;

[0025] Figure 2 These are schematic diagrams of the array configuration designed in this invention and a schematic diagram of the three-dimensional Cartesian coordinate system established under this array configuration, wherein... Figure 2 (a) is a schematic diagram of the array configuration designed in this invention. Figure 2 (b) is a schematic diagram of the three-dimensional Cartesian coordinate system constructed in this invention;

[0026] Figure 3 These are the directional and pitch dimension cross-sectional views of the subarray radiation pattern designed in the simulation experiment of this invention, wherein... Figure 3 (a) is a directional cross-sectional view of the subarray radiation pattern designed in this invention. Figure 3 (b) is a pitch dimension cross-section of the subarray pattern designed in this invention;

[0027] Figure 4 This is a top view in the XOY plane of the power spectrum of the subarray-level received signal obtained by the prior art and the present invention in the simulation experiment of the present invention, wherein, Figure 4 (a) is a top view of the power spectrum of the subarray-level received signal obtained by the prior art in the XOY plane. Figure 4 (b) is a top view of the power spectrum of the subarray level received signal obtained by the present invention in the XOY plane;

[0028] Figure 5 This is a pitch-dimensional side view of the average output signal-to-noise ratio loss after subarray-level adaptive beamforming of the received signals obtained by the prior art and the present invention in the simulation experiment of the present invention. Figure 5 (a) is a pitch-dimensional side view of the average output signal-to-noise ratio loss after subarray-level adaptive beamforming of the received signal obtained by the prior art. Figure 5 (b) is a pitch-dimensional side view of the average output signal-to-noise ratio loss after subarray-level adaptive beamforming of the subarray-level received signal obtained in this invention. Detailed Implementation

[0029] The implementation steps of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0030] Reference Figure 1 The specific implementation steps of the present invention will be further described below with reference to the embodiments.

[0031] Step 1: Generate a planar array signal including grid lobe angle interference signal and noise.

[0032] In the embodiments of the present invention, the number of array elements in the two-dimensional planar array is 64, and the array element arrangement is 8×8.

[0033] Reference Figure 2 The three-dimensional Cartesian coordinate system of the two-dimensional planar array of the present invention will be further described below.

[0034] A three-dimensional Cartesian coordinate system is established for the planar array, with the center of the array as its origin. The z-axis represents the direction from the center of the array to the center of the first row of linear arrays. The plane formed by the x and y axes is perpendicular to the z-axis. The distances from the center of the array along the x, y, and z axes represent the distances of the array elements along the x, y, and z axes, respectively. The distances of each array element in the planar array along the x, y, and z axes in the three-dimensional Cartesian coordinate system represent the element's position information. θ in the three-dimensional Cartesian coordinate diagram represents the azimuth angle of the signal, defined as the angle between the projection of the signal onto the XOY plane in the three-dimensional Cartesian coordinate system and the x-axis of the coordinate system. The pitch angle of the signal is defined as the angle between the signal and the XOY plane of the three-dimensional Cartesian coordinate system.

[0035] The planar array signal generated by this invention is used to calculate the weights used when designing the subarray radiation pattern. In the embodiments of this invention, the generated planar array signal contains 100 grating lobe interference signals. The angles of these 100 grating lobe interference signals are selected from the grating lobe angle region corresponding to the subarray radiation pattern.

[0036] The planar array signal is generated using the grid lobe angle interference signal and white noise as follows:

[0037] X = AS + N

[0038]

[0039]

[0040]

[0041] Where X represents the planar array signal, A represents the signal steering matrix, the columns of which represent the steering vectors of interference signals at different grating lobe angles, S represents the signal complex envelope matrix, the rows of which represent the complex envelope vectors of interference signals at different grating lobe angles, each vector being a random vector of a standard normal distribution generated by the simulation software MATLAB R2020b, and N represents the white noise signal. Let θ represent the azimuth angle of the interference signal in the i-th grating lobe. i and pitch angle The guide vector, i represents the index of the grating lobe interference signal, i = 1, 2, ..., P, P represents the total number of grating lobe interference signals, exp(·) represents the exponential operation with the natural constant e as the base, j represents the sign of the imaginary part of the complex number, π represents pi, λ represents the wavelength of the electromagnetic wave, r represents the position vector of the array element in the planar array, the superscript T represents the transpose operation, k represents the beam vector of the grating lobe angle interference signal in the three-dimensional Cartesian coordinate system, cos represents the cosine operation, and sin represents the sine operation.

[0042] Step 2: Calculate the weight of each subarray after the planar array is uniformly divided.

[0043] The planar array in this embodiment of the invention is divided into four subarrays evenly by the horizontal and vertical lines at the center of the planar array, with each subarray containing 16 array elements.

[0044] Step 2.1, calculate the autocorrelation matrix of each subarray signal according to the following formula:

[0045]

[0046] Among them, R m Let X represent the autocorrelation matrix of the m-th subarray signal. The m-th subarray signal refers to the signal portion corresponding to the array element within the m-th subarray of the planar array signal. m represents the index of the uniformly divided subarray of the planar array, m = 1, 2, ..., M, where M represents the number of uniformly divided subarrays of the planar array, N represents the number of sampling points for each subarray signal, and ∑ represents the summation operation. m (n) represents the nth sampled data of the mth subarray signal, where n represents the sampling sequence number of the subarray signal, n = 1, ..., N, and the superscript H indicates the conjugate transpose operation.

[0047] Step 2.2, according to the following formula, obtain the steering vector corresponding to different azimuth and elevation angles for the desired signal received by each array element in the subarray:

[0048]

[0049]

[0050] in, This indicates that the desired signal received by the array element in the m-th subarray corresponds to an azimuth angle of θ0 and an elevation angle of θ0. The guide vector, r m Let represent the position vector of the array element in the m-th subarray, and k0 represent the beam vector of the desired signal in the three-dimensional Cartesian coordinate system.

[0051] Step 2.3: Calculate the weights of each subarray using the MVDR method:

[0052]

[0053] Among them, w m This represents the weight of the m-th subarray, and the superscript -1 indicates the inversion operation.

[0054] Step 3, design the orientation pattern for each subarray:

[0055] Step 3.1, calculate the response amplitude of each subarray for each azimuth and elevation angle within the observation angle range according to the following formula:

[0056]

[0057] in, This indicates that the m-th subarray corresponds to an azimuth angle of θ' and an elevation angle of θ'. The response amplitude, This indicates that the azimuth angle θ' and elevation angle of the signal received by the array element in the m-th subarray are respectively... The guide vector.

[0058] Step 3.2: Connect the response amplitudes of each subarray to each azimuth and elevation angle in sequence within the observation angle range of [-90°, 90°] for both azimuth and elevation angles to obtain the radiation pattern of that subarray.

[0059] Since the weights of each subarray are calculated using the MVDR method, the principle of which is to ensure that the desired signal received by the array can be output without loss, while constraining the total power of the array output signal to be minimized, thereby achieving the effect of suppressing interference. Using the weights obtained by this method to design the array pattern can create nulls at the interference angles. In this embodiment of the invention, the generated planar array signal contains 100 grating lobe angle interference signals. Using this planar array signal and the weights obtained by the MVDR method to design the subarray pattern can create wide nulls at the grating lobe angles corresponding to the subarray level pattern.

[0060] Step 4: Suppress grid lobe interference.

[0061] A subarray with a wide null in the subarray pattern grating lobe angle is used to receive the incoming signal and suppress grating lobe interference in the incoming signal. The implementation process is as follows:

[0062] Step 3.1: Establish the dimension reduction transformation matrix as follows. The number of rows in this matrix equals the number of array elements in the planar array, and the number of columns equals the number of subarrays into which the planar array is divided. In this embodiment of the invention, the planar array has a total of 64 array elements, which are uniformly divided into 4 subarrays, each containing 16 array elements. The first 16 elements in the first column of this matrix represent the weight coefficients corresponding to the array elements of the first subarray. The elements from the 17th to the 32nd elements in the second column represent the weight coefficients corresponding to the array elements of the second subarray. The elements from the 33rd to the 48th elements in the third column represent the weight coefficients corresponding to the array elements of the third subarray. The elements from the 49th to the 64th elements in the fourth column represent the weight coefficients corresponding to the array elements of the fourth subarray.

[0063]

[0064] Where T represents the dimension reduction transformation matrix, w1 = [w 1,1 ,…,w 1,l ,…,w 1,16 ] T w 1l The weight coefficient of the l-th element in the first subarray is represented by l, where l represents the index of the element in the subarray, l = 1, 2, ..., L, and L represents the number of all elements in each subarray. In the embodiment of the present invention, L = 16.

[0065] Step 3.2: According to the following formula, multiply the weight coefficients in the weights of each subarray with the incoming signal received by the corresponding array element in the subarray of the received signal received by the planar array to obtain the subarray-level received signal, thereby suppressing grating lobe interference in the incoming signal:

[0066] X sub =T H X

[0067] Among them, X sub X(n) represents the received signal of the subarray level.

[0068] The effects of this invention will be further illustrated below with simulation experiments:

[0069] 1. Simulation experimental conditions:

[0070] The hardware platform for the simulation experiment of this invention is: Intel(R) Core(TM) i7-10700 CPU with a main frequency of 2.90GHz and 16GB of memory.

[0071] The software platform for the simulation experiment of this invention is: Windows 10 operating system and MATLAB R2020b.

[0072] The simulation parameters of this invention are set as follows: a two-dimensional planar array with 64 elements, an 8×8 array arrangement, a radar operating wavelength λ = 0.015m, an element spacing d = 0.0075m, a carrier frequency f0 = 26GHz, a sampling snapshot count of 1000, a target signal source of 1, an azimuth angle θ0 = 0°, and a target signal elevation angle of 0°. The signal-to-noise ratio is set to -10dB.

[0073] 2. Simulation content and result analysis:

[0074] The simulation experiment of this invention uses the method proposed in this invention to design the subarray radiation pattern of a planar array uniformly divided into subarrays, thereby suppressing grating lobe interference. In the simulation of this invention, the planar array is uniformly divided into 4 subarrays. For a target signal from the normal direction, the grating lobes of its subarray-level radiation pattern appear in eight angular regions with azimuth and elevation angles of (30, 0)(0, 30)(-30, 0)(0, -30)(33, 33)(33, -33)(-33, 33)(-33, -33). Since the four angular regions of (33, 33)(33, -33)(-33, 33)(-33, -33) are in the subarray before optimization... The radiation pattern shows nulls, so when designing the subarray radiation pattern, it is only necessary to form wide nulls in the four angular regions of (30, 0), (0, 30), (-30, 0), and (0, -30). Therefore, when generating the planar array signal, with the angles (30, 0), (0, 30), (-30, 0), and (0, -30) as the center, an interference signal is set at 0.5° intervals in square angular regions of 2° in both the azimuth and elevation dimensions, for a total of 100 grating lobe angle interference signals, with an interference-to-noise ratio (INR) of 30dB for each. Since the amplitude and phase errors of the generated signals in the simulation experiment are random, the calculated output SNR loss after the subarray-level adaptive beamforming is also random. Therefore, 100 simulation experiments are performed when calculating the SNR loss, and the average of the simulation results is taken. The azimuth and elevation cross-sectional views of the subarray radiation pattern designed in step 3 are generated using the simulation software MATLAB R2020b, and the results are as follows. Figure 3 As shown. Within the observation angle range of [-90°, 90°] for both azimuth and elevation angles, 721 angles are uniformly selected in each dimension. The power value of the subarray-level received signal at each angle is calculated. By connecting the power values ​​of the subarray-level received signal at each angle within the observation angle range of [-90°, 90°], the power spectrum of the subarray-level received signal is obtained. The power spectrum of the subarray-level received signal in step 4 is generated using the simulation software MATLAB R2020b. The result is shown in the figure. Figure 4As shown in (b), subarray-level adaptive beamforming is performed using the received signal with suppressed grating lobe interference. Within the azimuth and elevation angles of [-40°, 40°], the interference signal angle is selected at 1° intervals in each dimension. In the simulation of this invention, subarray-level adaptive beamforming was performed 100 times on the interference signal at each angle, resulting in 100 output signal-to-noise ratio (SNR) results. The average output SNR corresponding to each interference signal angle is obtained by averaging the average output SNR for each interference signal angle. This average is then subtracted from the ideal output SNR to obtain the output SNR loss value. These values ​​are then concatenated using the simulation software MATLAB R2020b within the azimuth and elevation angles of [-40°, 40°] to obtain the output SNR loss diagram of subarray-level adaptive beamforming against different interference angles. The results are as follows: Figure 5 As shown in (b).

[0075] The following is combined with Figure 3 , Figure 4 and Figure 5 The effects of the present invention will be further described.

[0076] Figure 3 This is the design subarray radiation pattern obtained in the simulation experiment of this invention, wherein, Figure 3 (a) is the azimuth cross-section diagram. The horizontal axis is the directional dimension angle, with the unit being degrees (°). The vertical axis is the amplitude of the directional diagram, with the unit being dB. Figure 3 (b) is a pitch dimension cross-sectional view. The horizontal axis is the pitch dimension angle, and the unit is degrees (°). The vertical axis is the amplitude of the radiation pattern, and the unit is dB.

[0077] Figure 4 This is a top view of the power spectrum of the subarray-level received signal obtained in the simulation experiment of this invention in the XOY plane, wherein, Figure 4 (a) is the power spectrum of the subarray-level received signal obtained by existing technology. Figure 4 (b) is the power spectrum of the subarray level received signal obtained by the method proposed in this invention. Figure 4 The horizontal axis represents the pitch dimension in degrees (°), and the vertical axis represents the direction dimension in degrees (°).

[0078] Figure 5 This is a pitch-dimensional side view of the subarray-level adaptive beamforming's average output signal-to-noise ratio loss against different interference angles, obtained from the simulation experiment of this invention. Figure 5 (a) is a graph showing the average output signal-to-noise ratio loss curve of subarray-level adaptive beamforming against different interference angles obtained by existing technology. Figure 5 (b) is a graph showing the average output signal-to-noise ratio loss of subarray-level adaptive beamforming against different interference angles obtained by the method proposed in this invention. Figure 5The horizontal axis represents the pitch angle, measured in degrees (°), and the vertical axis represents the output signal-to-noise ratio loss, measured in dB.

[0079] In simulation experiments, the existing technologies used refer to:

[0080] The prior art refers to the method for receiving signals at the synthetic subarray level proposed by the 27th Research Institute of China Electronics Technology Group Corporation in its patent application document "A digital beamforming method for solving the problem of grating lobe interference" (application number 201611244720.8, application date 2016.12.29, application publication number CN 106842147 A).

[0081] Depend on Figure 3 Simulation results show that this method creates nulls in the four grating lobe angle regions (30, 0), (0, 30), (-30, 0), and (0, -30) on the subarray radiation pattern, with a null depth of up to -40 dB, which can reduce the power of interference signals entering from the grating lobe angles. Figure 4 Simulation results show that, compared to existing technologies, after synthesizing the subarray using the dimensionality reduction transformation matrix obtained in this invention, the grating lobe interference signal power in the subarray-level received signal is reduced by approximately 15 dB. Figure 5 The simulation results show that, compared with the existing technology, the method proposed in this invention reduces the average output signal-to-noise ratio loss of subarray-level adaptive beamforming against grating lobe angle interference by about 7dB after suppressing grating lobe interference, that is, the average output signal-to-noise ratio is improved by 7dB.

Claims

1. A method for suppressing grating lobe interference based on subarray radiation patterns, characterized in that, The method involves calculating the weights of each subarray using a planar array signal containing grating lobe angle interference and noise, based on the minimum variance distortionless response method. These weights are then used to design the subarray radiation pattern, creating a wide null at the corresponding grating lobe angle in the subarray-level radiation pattern, thereby suppressing grating lobe interference. The steps of this method are as follows: Step 1: Generate a planar array signal including grid lobe angle interference signal and noise; Step 2: Calculate the weight of each subarray after uniformly dividing the planar array: Step 2.1, calculate the autocorrelation matrix of each subarray signal: ； in, Indicates the first The autocorrelation matrix of the subarray signals, the th The subarray signal refers to the signal in the planar array. The signal portion corresponding to each array element within a subarray. This indicates the index of the subarray that is uniformly divided in a planar array. M represents the number of subarrays that are uniformly divided into in a planar array. This indicates the number of sampling points for each subarray signal. This represents the summation operation. Indicates the first The first subarray signal Secondary sampling data, Indicates the sampling sequence number of the subarray signal. ; Step 2.2, calculate the steering vector corresponding to different azimuth and elevation angles for the desired signal received by each array element in each subarray: ； ； in, Indicates the first The azimuth angle corresponding to the desired signal received by each element in the subarray is... and pitch angle The guide vector, Indicates the first The position vectors of the array elements within each subarray This represents the beam vector of the desired signal in a three-dimensional Cartesian coordinate system. Step 2.3, calculate the weight of each subarray: ； in, Indicates the first The weights of each subarray, with the superscript -1 indicating the inversion operation; Step 3, design the orientation pattern for each subarray: Step 3.1, calculate the response amplitude of each subarray for each azimuth and elevation angle within the observation angle range according to the following formula: ； in, Indicates the first Each subarray corresponds to an azimuth angle of... and pitch angle The response amplitude, Indicates the first The weights of each submatrix, with the superscript H indicating the conjugate transpose operation. Indicates the first The azimuth angle of the signal received by each element in the subarray is... and pitch angle The guide vector; Step 3.2, calculate the response amplitude of each subarray for each azimuth and elevation angle, where both azimuth and elevation angles are... The radiation pattern of the subarray is obtained by connecting the lines sequentially within the observation angle range; Step 4, suppress grid lobe interference: Step 4.1: Establish a dimension reduction transformation matrix. The number of rows in this matrix is ​​equal to the number of array elements in the planar array, and the number of columns in this matrix is ​​equal to the number of subarrays into which the planar array is divided. Step 4.2: According to the subarray synthesis formula, the elements in the weight of each subarray are multiplied and accumulated with the incoming wave signal received by the corresponding array element in the subarray of the incoming wave signal received by the planar array to obtain the subarray-level received signal, thereby suppressing the grating lobe interference in the incoming wave signal.

2. The grating lobe interference suppression method based on subarray radiation pattern according to claim 1, characterized in that, The planar array signal mentioned in step 1 is obtained by the following formula: ； ； ； ； in, Represents a planar array signal. This represents the signal steering matrix, where each column represents the steering vector of the interference signal at different grating lobe angles. This represents the complex envelope matrix of the signal. The rows of this matrix represent the complex envelope vectors of interference signals at different grating lobe angles. Each vector is a random vector following a standard normal distribution, generated using the simulation software MATLAB R2020b. Represents white noise signal, The azimuth angle of the interference signal in the i-th grating lobe is . and pitch angle The guide vector, , This indicates the total number of grid lobe interference signals. Represented by natural constant The exponential operation with base 0, where j denotes the sign of the imaginary part of the complex number. Represents pi (π). The wavelength of an electromagnetic wave The superscript represents the position vector of an element within a planar array. This indicates the transpose operation. This represents the beam vector of the grating lobe angle interference signal in a three-dimensional Cartesian coordinate system. This indicates the cosine operation. This indicates the sine-taking operation.

3. The grating lobe interference suppression method based on subarray radiation pattern according to claim 1, characterized in that, The subarray synthesis formula described in step 4.2 is as follows: ； in, This indicates the received signal at the subarray level. Represents the dimension reduction transformation matrix. This represents the received signal of the planar array.

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